Open charm reconstruction in the ALICE experiment

1
Open charm reconstruction in the ALICE experiment

• Elena Bruna
• Supervisor Prof. Massimo Masera

Seminar for the end of 2nd year (XIX) Torino,
Dec 2nd 2005
2
Outline

• Physics motivations of open charm analysis in
  Heavy Ion Collisions
• D ? K-pp overview of the kinematics
• Measurement of open charm in the ALICE
  experiment
• Exclusive reconstruction of D ? K-pp
• Event generation and reconstruction
• Reconstruction of the secondary vertex
• Selection strategy
• Perspectives for the measurement of D elliptic
  flow
• Summary and work plans

3
Motivations for the Open Charm physics in Heavy
Ion Collisions
4
Heavy quarks as probes of nuclear medium /1

• charm, bottom produced at early stages of the
  collision (timescale 1/mQ lt ?QGP 10 fm at
  LHC)
• Studies of initial state effects nuclear
  shadowing
• Because of the very low x down to 10-4 at
  LHC the so many gluons merge together, affecting
  the partons densities at low x w.r.t. protons
  partons ones.
• thermal production
• ? The c quark might be produced in the plasma
  phase mc ( 1.2 GeV) comparable with
  predicted Tplasma ( 0.6-0.8 GeV)
• open QQ production (not Drell-Yan) natural
  normalization for QQ studies
• ? Quarkonia enhancement at low PT and
  suppression at high PT.

5
Heavy quarks as probes of nuclear medium /2

• charm, bottom have long lifetime (gt ?QGP ) and
  can probe the bulk, strongly interacting phase
• Studies of final state effects
• 1) radiative energy loss
• Hard partons radiate gluons in the medium, lose
  energy and become
• quenched. Heavy quarks are expected to lose less
  energy than light
• quarks.
• High ?E ? suppression of the produced
  particles (at high PT) ? RAA?1

Nuclear modification factor
It depends on the properties of the medium (gluon
density, temperature and volume), it provides
information on such properties.
6
Heavy quarks as probes of nuclear medium /3

• Studies of final state effects
• 2) anisotropic flow on the transverse plane
• Elliptic Flow collective motion of
  particles (due to high pressure arising from
  compression and heating of nuclear matter)
  superimposed on top of the thermal motion

Correlation between azimuthal angles ? of
outgoing particles and the direction of the
impact parameter (REACTION PLANE ?RP)
Elliptic flow coefficient
High opacity of the medium (strongly interacting)
? high anisotropic flow ? high v2
v2 provides information on the opacity of the
medium.
7
Few experimental results from RHIC /1

• radiative energy loss - RAA of the D mesons
• (? PT spectra of ee- from D semileptonic decays
  )

from QM05
from QM05

• Charm is suppressed! Suppression is
  approximately the same as for hadrons.
• Challenge for energy loss models.

Also pp and pA data are needed as reference!
8
Few experimental results from RHIC /2

• anisotropic flow v2 of the D mesons
• (? f spectra of ee- from D semileptonic decays )

from QM05
from QM05

• Significant flow of charm quark as for light
  quarks
• ? Strong coupling of charm quark to the
  medium
• Indication for reduction of v2 at pT gt 2 GeV/c
  
• (PHENIX)

Also pp and pA data are needed as reference!
9
D ? K-pp overview of the kinematics
10
Why D ? K-pp ?
Advantages

1. D has a long mean life (311mm compared to
   123 mm of the D0)
2. D ? K-pp is a 3-charge body decay ? the most
   promising from an experimental point of view
3. D ? K-pp has a relatively large branching
   ratio (BR9.2 compared to 3.8 for D0 ? K-p).

drawbacks

1. Combinatorial background for this 3-body channel
   is larger than for D0 ? K-p.
2. The average PT of the decay product is softer (
   0.7 GeV/c compared to 1 GeV/c)

11
Hadronic 3-charge-body decays of D

D?K-?? BR 9.2
D?K-pp Non Resonant BR 8.8
D?K0(892)p?K-pp Resonant BR 1.3
D?K0(1430)p?K-pp Resonant BR 2.3
D?K0(1680)p?K-pp Resonant BR 3.810-3
12
Kinematics (1)
K
PT distributions of the generated particles (ONLY
PYTHIA generation, NO propagation and
reconstruction in the detector) (nonresonant
events)
Mean 0.87 GeV/c
D
Mean 1.66 GeV/c
?
Mean 0.67 GeV/c
Knowledge of the PT shapes of the decay products
important at the level of the selection strategy
13
Kinematics (2)
p
Comparing with Pb-Pb central events (ONLY HIJING
generation, NO propagation and reconstruction in
the detector) PT distributions
Mean 0.67 GeV/c Mean 0.50 GeV/c
nonresonant D decay
K
HIJING central (normalized)
Mean 0.87 GeV/c Mean 0.65 GeV/c
K and p from D are harder than K and p produced
in a Pb-Pb event
14
Dalitz Plots Kinematics (3)
Non resonant
Resonant
15
Measurement of open charm in the ALICE experiment

16
Time Projection Chamber (TPC) Tracking, PID
(dE/dx) -0.9lt?lt0.9
ALICE _at_ LHCsetup
HMPID
TRD
MUON SPECTR..
PHOS
Inner Tracking System (ITS) 6 SILICON layers
(pixel, drift, strip) Vertices reconstruction,
PID (dE/dx) -0.9lt?lt0.9
Time Of Flight (TOF) Tracking, PID
(time) -0.9lt?lt0.9
Size 16 x 26 m Weight 10,000 tons
17
Track Impact Parameter d0
SIGMA (fit)
expected d0 resolution (s)
d0 d0 sim
MEAN (fit)
0.4ltPtlt0.6 GeV/c
18
Track Impact Parameter d0 pull
SIGMA (fit)
Calculate the pull
MEAN (fit)
19
Exclusive reconstruction of D ? K-pp
20
Simulation strategy
Our purpose exclusive reconstruction of D in
the ALICE barrel (Inner Tracking System employed
in the search for secondary vertexes)
Too large statistics (108 events) would be
required to study the signal!!
Central Pb-Pb event (blt3.5 fm, dN/dy 6000,
vs5.5 TeV)
9 D/D- in ylt1
Signal and background events separately generated
with the Italian GRID

• 5000 signal events with only D decaying in Kpp
  (using PYTHIA)
• Check the kinematics and the reconstruction
• Optimize the vertexing algorithm
• 20000 background events (central Pb-Pb events
  using HIJING)
• cc pairs merged in addition in order to reproduce
  the charm yield predicted by NLO pQCD
  calculations ( 118 per event)
• Tune the cuts (impact parameter cut,) on the
  tracks to be analyzed by the vertexing algorithm
• Evaluate the combinatorial background

21
Reconstructed signal events Dalitz Plots
From reconstructed tracks ( the info
given by the generation are taken into account)
This is done as an internal cross-check procedure
22
Reconstructed signal events D invariant mass
Mean
Integrated over PT
MEAN 1.867 GeV/c2 RMS 0.019 GeV/c2
this is not a complete
reconstruction of the signal tracks are grouped
by means of info. stored at generation time.
MINV Resolution (SIGMA of the gaussian fit)
Knowledge of MINV resolution vs PT is important
when selecting the signal candidates
23
Reconstruction of the secondary vertex for D ?
K-pp

• First idea adapting and improving the method
  already written for the primary vertex finding
  and fitting in p-p
• Second idea writing a new secondary vertex
  finder and comparing its performace with the
  previous ones

24
Vertex finder

• Originally developed to find the primary vertex
  in p-p
• Based on the Straight Line Approximation of a
  track (helix)
• Main steps
• The method receives N (N3 in our case) tracks as
  input
• Each track is approximated by a straight line in
  the vicinity of the primary vertex
• An estimation of the secondary vertex from each
  pair of tracks is obtained evaluating the
  crossing point between the 2 straight lines
• The coordinates of secondary vertex are
  determined averaging among all the track pairs

25
Improving the Straight Line Vertex Finder

• Add a cut on the distance of closest approach
  (DCA) between the two straight lines
• A pair of tracks is not used for the vertex
  estimation if their distance of closest approach
  is gt fDCAcut
• Use a weighted mean of the 2 DCA points
• In order to take into account the errors on the
  tracks parameters
• Calculate a parameter representing the dispersion
  of the vertices given by the track pairs (fSigma)

26
DCA cut effect
No DCAcut
X coord
RMS179 µm
Finder- MC (mm)
Y coord
RMS183 µm
Finder- MC (mm)
Z coord
RMS166 µm
Finder- MC (mm)
27
Weighted mean effect
Arithmetic mean
X coord
RMS179 µm
Finder- MC (mm)
Y coord
RMS183 µm
Finder- MC (mm)
Z coord
RMS166 µm
Finder- MC (mm)
28
Vertices dispersion

• Dispersion fSigma standard deviation of the 3
  vertex estimations obtained from each track pair

29
Cutting on fSigma

• A cut fSigma lt 0.4 cm cuts 0.5 of the events and
  30 of the overflows and underflows (i.e. events
  for which the VertexFinder misses the true vertex
  by more than 1 mm)

• A cut fSigma lt 0.07 cm (700 mm) cuts 6.4 of the
  events and gives a RMS of 151 mm (for X
  coordinate)

30
Another improvement Helix vertex
finder

• Based on the Distance of Closest Approach (DCA)
  between helices
• Does not use a Straight Line Approximation as the
  old one
• Main steps
• The method receives N (N3 in our case) tracks as
  input
• For each pair of tracks, the coordinates of the 2
  points of closest approach are calculated
• An estimation of the secondary vertex from each
  pair of tracks is obtained averaging the
  coordinates of the points defining the DCA.
• Two different implemetations arithmetic vs.
  wieghted mean
• The coordinates of secondary vertex are
  determined averaging among all the track pairs
• The dispersion of the vertices given by the track
  pairs is calculated

31
Results from the helix finder
Straight Line Finder
X coord
RMS179 µm
Finder- MC (mm)
Y coord
RMS183 µm
Finder- MC (mm)
Z coord
RMS166 µm
Finder- MC (mm)
32
DCA cut effect on helix finders
fDCAcut1 cm
X coord
X coord
RMS169 µm
Finder- MC (mm)
Y coord
RMS171 µm
Finder- MC (mm)
Z coord
Z coord
RMS162 µm
Finder- MC (mm)
33
Weighted mean effect on helix finder
Arithmetic mean
X coord
RMS169 µm
Finder- MC (mm)
Y coord
RMS171 µm
Finder- MC (mm)
Z coord
RMS162 µm
Finder- MC (mm)
34
Vertices dispersion on Helix Finder

• Same distribution as for Straight Line finder

35
Cutting on fSigma

• A cut fSigma lt 0.4 cm cuts 0.5 of the events and
  35 of the overflows and underflows (i.e. events
  for which the VertexFinder misses the true vertex
  by more than 1 mm)

• A cut fSigma lt 0.07 cm (700 mm) cuts 5.6 of the
  events and gives a RMS of 140 mm (for X
  coordinate)

36
New secondary vertex finder
Straight Line Approximation used ? analytic method
Vertex coordinates (x0,y0,z0) from minimization
of
Where d1,d2,d3 are the distances (weighted with
the errors on the tracks) of the vertex from the
3 tracks
P1 (x1,y1,z1)
SecondaryVertex (x0,y0,z0)
sx sy
d1
37
Resolution of the vertex finder
RMS x
RMS y
At high Pt of D (Ptgt5-6 GeV/c), the RMS in the
bending plane increases, instead of going down to
15µm (spatial pixel resolution) as expected.
RMS z
Conclusion New method improves RMS of 40µm for
PtD 2GeV/c for x, y and z with respect to
previous Helix vertex finder based on DCA of
pairs of tracks.
38
Resolution at high Pt /1

• Checks with events only made of pions show that
  the RMS on the bending plane
• Decreases down to 50 µm if the 3 tracks have Pt
  2 GeV/c
• Reaches a value of 20 µm (in agreement with
  spatial pixel resolution) if the 3 tracks have Pt
  100 GeV/c

3 pion vertex RMS in the bending plane vs. Pt
39
Resolution at high Pt /2
In the signal events, as the Pt of the D
increases, the daughters become more and more
co-linear, resulting in a worse resolution along
the D direction.
p
p
K-
bending plane
D
40
Resolution in the rotated frame /1
Along the Pt of the D (x coord.)
Orthogonal to the Pt of the D (y coord.)
? Along the Pt of the D as Pt increases (for
Ptgt5-6 GeV/c) the angles between the decay
tracks become smaller in this coordinate the RMS
increases ? Orthogonal to the Pt of the D the
RMS decreases as expected
41
Resolution in the rotated frame /2
Ratios
42
Vertices dispersions/1
?x XVertex FOUND XVertex MC
?x lt 1000 µm
1000lt?x lt3000 µm
3000lt?x lt5000 µm
?x gt 5000 µm
fSigma bigger for bad vertices
fSigma (cm)
43
Vertices dispersions/2
Cut on fSigma
(for X coordinate)
Vertices taken / Vertices Tot (True vertices)
Fake vertices (tracks coming from 3
different D vertices)
RMS x (µm)
Mean x (µm)

• fSigma lt 0.7 cm cuts 1 of the events and gives
  a RMS of 130 µm

• fSigma lt 0.5 cm cuts 6 of the events and gives
  a RMS of 110 µm

44
Conclusions on the finders

• The Straight Line vertex finder
• DCA cut negligible effect on the RMS of the
  residual distributions, slightly reduced number
  of overflows and underflows
• The use of a weighted mean improves Z resolution
  by 6 mm
• Cutting on the dispersion fSigma removes the
  events for which the VertexFinder misses the true
  vertex by more than 1 mm and improves the
  resolution

• The Helix vertex finder
• Has better resolution w.r.t. Straight Line
  finder (by approximately 10 mm)
• Has less overflows and underflows w.r.t.
  Straight Line finder
• DRAWBACK the DCA between helices is obtained by
  minimization
• DCA cut, weighted mean and fSigma cut improve
  the resolution

• The Minimum Distance vertex finder
• Has better resolution w.r.t. Helix finder (by
  approximately 30 mm)
• Has less overflows and underflows w.r.t.
  previous finders
• Is an analytic method
• Weighted mean and fSigma cut improve the
  resolution
• Is presently THE candidate for first D analysis

A cut on fSigma has to be tuned (it can be done
at analysis level)
45
D selection strategy
46
Tuning the cuts
GOAL tune the cuts on both signal and background
events and find the cuts giving the best S/B.
(S/B 11 was found for the D0?K-p)

• CUT TIPOLOGIES
• On the single tracks used to feed the vertexer
  (Particle Identification, pT, track impact
  parameter)
• ? reduce the number af all the possible
  combinations of track-triplets in a central Pb-Pb
  collision ( 1010 without any initial cut!!). It
  MUST be cut by 4-5 orders of magnitude before
  using the more time-consuming vertexer.
• In progress.
• Once the triplets are combined, additional cuts
  (invariant mass and eventually pT, impact
  parameter) are mandatory before using the
  vertexer. These cuts are done on the triplets.
  
• To be done.
• The third kind of cuts is applied on the quality
  of the secondary vertices found (vertex
  dispersion-fSigma, pointing angle,)
• To be done.

47
Single track cuts /1
GOAL find a compromise between the number of
background triplets and the number of signals we
want to take
HOW for each triplet (both signal and bkg) a
loop on all the possible cuts (d0,Pt p,Pt K) is
done
  SIGNAL TAKEN Pt cut p (GeV/c)  Pt cut K (GeV/c)   d0 cut (mm)  MINIMUM Triplet BKG taken 
1 - 2 1,200 1,175 120 131
3 - 4 0,875 0,775 95 77.000
4 - 5 1,400 1,150 0 250.000
15 - 20 1,000 0,800 0 7.600.000
25 - 30 0,750 0,550 0 100.000.000
45 - 50 0,525 0,350 0 1.000.000.000
75 - 80 0,350 0,325 0 6.000.000.000
90 - 95 0,275 0,300 0 10.000.000.000
Cut on the track impact parameter (d0)
Particle Id. given by the generation initial
approach
The number of BKG triplets is reduced by a factor
of 100 when doing the cut on the Invariant Mass
within 3s (see slide 22)
48
Single track cuts /2
 Triplet BKG Pt cut p (GeV/c)  Pt cut K (GeV/c)   d0 cut (mm)  MAX signal taken 
101 - 102 1,325 1,200 105 0,9
104 - 105 0,900 0,800 85 3,1
105 - 106 1,225 1,000 0 6,0
106 - 107 0,975 0,775 0 11,0
107 - 108 0,750 0,600 0 19,4
1010 1011 0,000 0,000 0 100,0
The number of BKG triplets is reduced by a factor
of 100 when doing the cut on the Invariant Mass
within 3s (see slide 22)
BkgTriplets
No cut on the track impact parameter (d0)
Cut on d0 ? lower cuts on Pt (useful up to Bkg
105)
Particle Id. given by the generation initial
approach
49
Tuning the single track cuts /2
When tuning a cut, one has to keep in mind how
the Pt distribution of the D is modified
Pt reconstructed D Mean2.5 GeV/c
Pt reconstructed D Pt cut (p) 0.75 GeV/c Pt
cut (K) 0.6 GeV/c Mean1.8 GeV/c
Ratio With cut / Wo cut
50
Perspectives for the measurement of D elliptic
flow
51
Measurement of v2
Elliptic Flow correlation of particle emission
angles with the reaction plane (i.e. w.r.t the
impact parameter of the collision)

• Calculate the 2nd order coefficient of Fourier
  expansion of particle azimuthal distribution
  relative to the reaction plane
• The reaction plane is unknown.
• Estimate the reaction plane from particle
  azimuthal anisotropy
• Yn Event plane estimator of the unknown
  reaction plane
• Calculate particle distribution relative to the
  event plane
• Correct for event plane resolution
• Resolution contains the unknown YRP
• Can be extracted from sub-events

Event plane resolution
52
Motivation and Method

• GOAL Evaluate the statistical error bars for
  measurements of v2 for D mesons decaying in Kpp
• v2 vs. centrality (pT integrated)
• v2 vs. pT in different centrality bins
• TOOL fast simulation
• Assume to have only events with signal
• Generate ND(Db, DpT) events with 1 D per event
• For each event
• Generate a random reaction plane (fixed YRP0)
• Get an event plane (with correct event plane
  resolution)
• Generate the D azimuthal angle (fD) according to
  the probability distribution p(f) ? 1 2v2 cos
  2(f-YRP)
• Smear fD with the experimental resolution on D
  azimuthal angle
• Calculate v'2(D), event plane resolution and
  v2(D)

53
D azimuthal angle resolution
MEAN
RMS
Average ? resolution 8 mrad 0.47 degrees
54
D statistics
bmin-bmax (fm) s inel Pb-Pb () Nevents (106) Ncc per event D yield per event
0-3 3.6 0.72 118 45.8
3-6 11 2.2 82 31.8
6-9 18 3.6 42 16.3
9-12 25.4 5.1 12.5 4.85
12-18 42 8.4 1.2 0.47
Nevents for 2107 Minimum Bias triggers (without
any requirement on the impact parameter of the
collision)
D selected after all the cuts is still missing
for the time being ? e1.5 (same as D0)
ND(Db, DpT) selected e D reconstructed
? Total number of ND(Db, DpT) selected
Normalized to 2107 Minimum Bias Events
55
Results v2 vs. centrality
2107 Minimum Bias events
bmin-bmax N(D)selected s(v2)
0-3 1070 0.024
3-6 2270 0.015
6-9 1900 0.016
9-12 800 0.026
12-18 125 0.09

• Error bars quite large
• Would be larger in a scenario with worse event
  plane resolution
• May prevent to draw conclusions in case of small
  anisotropy of D mesons

56
Results v2 vs. pT
2107 MB events
pT limits N(D)sel s(v2)
0-0.5 120 0.06
0.5-1 230 0.05
1-1.5 330 0.04
1.5-2 300 0.04
2-3 450 0.03
3-4 210 0.05
4-8 220 0.05
8-15 40 0.11
pT limits N(D)sel s(v2)
0-0.5 140 0.06
0.5-1 280 0.04
1-1.5 390 0.04
1.5-2 360 0.04
2-3 535 0.03
3-4 250 0.05
4-8 265 0.05
8-15 50 0.11
pT limits N(D)sel s(v2)
0-0.5 50 0.10
0.5-1 100 0.07
1-1.5 140 0.06
1.5-2 125 0.06
2-3 190 0.05
3-4 90 0.07
4-8 95 0.07
8-15 20 0.15
57
Summary and work plans

• Preparatory checks on the kinematics and on the
  reconstructed signal events completed
• Secondary Vertex completed
• the method of the Minimum Distance of 3 tracks is
  presently THE candidate for first D analysis
• cuts on fSigma will be tuned at the analysis
  level
• D analysis cuts
• the work on the cuts on single tracks to feed
  the vertexer is in progress Pt, impact
  parameter, PID.
• The work on the cuts in the triplets and on the
  secondary vertices has to be done.
• Analysis on D elliptic flow in progress